An Internet system for and method of automatic optimizing quantitative business objectives of sellers (advertisers) with synergistic pricing, promotions and advertisements, while simultaneously minimizing expenditure and discovery and optimizing allocation of advertising channels that optimize such objectives.
Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method of optimizing quantitative business objectives and targets of product or service sellers together with synergistic pricing, promotions and advertisements, including one or more of search engine-based advertising, Internet web-based on-line display advertising, and television (TV) advertising, the method comprising: operating, by the seller/advertiser, an automated, adaptive, real-time computer engine (seller automated engine, or SAEJ) capable of determining the optimal price that the market will bear at any point of time, and capable of computing such price in real-time in order to optimize the sellers business targets; evaluating, within the SAEJ, the sellers advertising needs in the context of current cost-per-click (CPC) or cost per thousand impressions (CPM) prices, of the status of said targets, and the current market conditions; triggering, by the SAEJ, advertisements in response to said evaluating, as and when appropriate, and computing bids in real-time, taking into consideration the expense associated with each bid, the current status of said targets, and the requisite pricing needed to optimize said targets; and automatically and optimally allocating advertising selections in real-time, thereby to optimize allocation of advertising to achieve said targets while minimizing expenditure.
2. The method of claim 1 wherein the optimal CPC/CPM bids are discovered and rank-ordered according to the contribution made by each towards meeting the seller's unique targets while simultaneously minimizing advertising expenditure in anticipation of receiving corresponding clicks or leads resulting in consequent business based on an expected conversion rate.
This invention relates to optimizing digital advertising bids, specifically for cost-per-click (CPC) and cost-per-impression (CPM) campaigns, to maximize business outcomes while minimizing advertising costs. The problem addressed is the inefficiency in traditional bidding strategies that fail to align with a seller's unique business targets, such as revenue, lead generation, or profit margins, while also overpaying for ad placements. The method involves dynamically determining and ranking optimal CPC and CPM bids based on their expected contribution to the seller's specific goals. This is done by evaluating how each bid influences the likelihood of achieving the desired business outcomes, such as clicks, leads, or conversions, while minimizing overall advertising expenditure. The system accounts for an expected conversion rate, ensuring that bids are not only cost-effective but also aligned with the seller's broader business objectives. By prioritizing bids that offer the highest return on investment, the method ensures that advertising spend is optimized for both immediate engagement and long-term business growth. This approach improves efficiency by reducing wasted ad spend and increasing the likelihood of achieving the seller's financial and operational targets.
3. The method of claim 2 wherein synergistic computation is affected by the SAEJ of the optimum product or service price for such advertising to further optimize said targets.
This method improves ad targeting by calculating the best price for a product or service and using that information to make the ads even more effective.
4. The method of claim 3 wherein the SAEJ adjusts such product or service price automatically and in real-time.
This invention relates to dynamic pricing systems for products or services, specifically addressing the challenge of manually adjusting prices in response to market conditions. The system uses a self-adjusting economic (SAEJ) mechanism to automatically and in real-time modify product or service prices based on predefined criteria. The SAEJ mechanism continuously monitors relevant factors such as demand, supply, competitor pricing, or other economic indicators. When a triggering condition is detected, the system recalculates the optimal price and updates it without human intervention. This ensures prices remain competitive and aligned with market dynamics, improving revenue and customer satisfaction. The system may also integrate with inventory management or sales data to further refine pricing adjustments. The invention aims to eliminate inefficiencies in static pricing models by enabling rapid, data-driven price optimization.
5. The method of claim 4 wherein the SAEJ automatically and appropriately adjusts ad placement, corresponding CPC bids, number of display ads with corresponding CPM, and simultaneous product or service price adjustment, all within unique seller-provided constraints.
This invention relates to automated advertising and pricing optimization within an online marketplace or e-commerce platform. The system addresses the challenge of dynamically adjusting ad placements, bid strategies, and pricing to maximize revenue while respecting seller-defined constraints. The method involves an automated system that continuously monitors ad performance, user engagement, and market conditions. It adjusts ad placements based on real-time data, ensuring high-visibility positions for high-performing ads while minimizing costs for underperforming ones. The system also modifies cost-per-click (CPC) bids to optimize ad visibility and cost-efficiency, ensuring competitive positioning without overspending. Additionally, the system controls the number of display ads shown and their cost-per-thousand-impressions (CPM) rates, balancing visibility and budget constraints. Simultaneously, it adjusts product or service prices in response to demand, competition, and ad performance, ensuring profitability while maintaining competitiveness. All adjustments are made within predefined seller constraints, such as maximum bid limits, price floors, or ad placement restrictions, ensuring alignment with business objectives. The system operates autonomously, eliminating manual intervention while adapting to market fluctuations and user behavior. This approach enhances ad effectiveness, improves conversion rates, and maximizes revenue for sellers.
6. The method of claim 5 wherein, following a short term ad promotion, reverting back to normal mode of operation for both CPC/CPM bids and also that of product or service pricing.
A method for managing digital advertising campaigns involves adjusting bidding strategies and pricing models after a short-term promotional period. The technique addresses the challenge of optimizing ad performance during promotions while ensuring a smooth transition back to standard operations. Initially, the system implements a temporary promotional mode where cost-per-click (CPC) or cost-per-impression (CPM) bids are adjusted to enhance visibility or conversion rates. Simultaneously, pricing for promoted products or services may be modified to align with the promotional strategy. After the promotion concludes, the system automatically reverts to the original bidding and pricing configurations, restoring normal campaign operations. This approach ensures that promotional adjustments do not disrupt long-term advertising performance or pricing strategies. The method may also include monitoring campaign metrics during the promotion to inform future adjustments. By dynamically managing bids and pricing, the system balances short-term promotional goals with sustained advertising efficiency.
7. The method of claim 4 wherein the SAEJ optimizes the sellers targets by computing optimal CPC/CPM advertising channel selection, placement and pricing as well as the optimal product or service pricing.
This invention relates to optimizing advertising and pricing strategies for sellers in digital marketing. The problem addressed is the inefficiency in selecting advertising channels, placements, and pricing, as well as determining optimal product or service pricing to maximize profitability. The solution involves a system that automates these decisions using data-driven optimization techniques. The system computes optimal cost-per-click (CPC) or cost-per-mille (CPM) advertising channel selection, placement, and pricing. It also determines the best pricing for the product or service being advertised. The optimization process considers multiple factors, including market demand, competitor pricing, and advertising performance metrics, to maximize return on investment (ROI) for sellers. The system dynamically adjusts these parameters in real-time based on evolving market conditions and performance data. By integrating advertising channel optimization with product pricing, the system ensures that sellers allocate their advertising budgets effectively while maintaining competitive pricing. This approach improves conversion rates and profitability by aligning advertising spend with the most effective channels and pricing strategies. The solution is particularly useful for e-commerce platforms, digital marketers, and businesses leveraging online advertising to drive sales.
9. The method of claim 7 wherein, beyond automatic price discovery, promotion and optimizing across said targets, the SAEJ is operated automatically to compute CPC bid values per product, per set of keywords, per ad placement, per search engine in real-time, all as a function of and synergistically with each of the CPC bid history, prevailing competitive CPC pricing, the sellers time-sensitive objectives and targets, and the prevailing market conditions.
This invention relates to automated digital advertising optimization, specifically for computing cost-per-click (CPC) bid values in real-time across multiple advertising platforms. The system addresses the challenge of dynamically adjusting bids to maximize advertising efficiency while aligning with time-sensitive business objectives and market conditions. The method operates an automated advertising engine (SAEJ) that computes CPC bid values for individual products, keyword sets, ad placements, and search engines. These computations are performed in real-time, integrating multiple factors: historical CPC bid data, current competitive pricing, the seller's time-sensitive goals, and prevailing market conditions. The system goes beyond basic price discovery and promotion optimization by synergistically analyzing these variables to determine optimal bid values. The approach ensures that bids are not only competitive but also strategically aligned with the seller's objectives, such as maximizing return on ad spend (ROAS) or achieving specific conversion targets. By continuously adjusting bids based on real-time market dynamics, the system enhances advertising performance while reducing manual intervention. This method is particularly useful in fast-moving digital advertising environments where manual bid adjustments are impractical.
10. The method of claim 7 wherein there is automatic computing of the optimum CPC bids for each search engine, for each set of key words, for each ad position for each product, and for selected geographical regions.
The method automatically calculates the best bid amount to pay for ads on different search engines, using different keywords, ad positions, products, and locations.
11. The method of claim 7 wherein there is automatic evaluating and ranking of the order of the prevailing CPC bids according to the contribution to the unique business targets, with minimum expenditure, and for each search engine, for each set of key words, for each ad position, for each product, and for selected geographical regions.
This invention relates to optimizing online advertising campaigns by automatically evaluating and ranking the effectiveness of Cost-Per-Click (CPC) bids across multiple search engines. The system addresses the challenge of maximizing advertising impact while minimizing costs by dynamically assessing how each CPC bid contributes to unique business objectives. The evaluation considers various factors, including search engine selection, keyword sets, ad positioning, product targeting, and geographical regions. By analyzing these variables, the system determines the most cost-effective bid strategies that align with specific business goals. The ranking process ensures that bids are prioritized based on their potential return on investment, allowing advertisers to allocate budgets efficiently. This approach automates the decision-making process, reducing manual effort and improving campaign performance by continuously adapting to changing market conditions and user behavior. The solution is particularly useful for businesses running large-scale advertising campaigns across different platforms, as it provides a data-driven method to optimize bid strategies in real-time.
12. The method of claim 10 wherein the CPC bids are automatically computed in real-time as a function of the seller's targets, including revenue, profit, product inventory, supplier's break, current target status as a function of time, desired relative degree of emphasis at that time, and the competitive market pricing for CPC for the desired ad placement.
This invention relates to dynamic pricing optimization for cost-per-click (CPC) advertising in online marketplaces. The problem addressed is the need for automated, real-time adjustment of CPC bids to maximize seller performance while considering multiple competing objectives. Traditional static bidding strategies fail to adapt to changing market conditions, inventory levels, or seller targets, leading to suboptimal ad placement and revenue. The method automatically computes CPC bids in real-time based on a seller's targets, including revenue, profit, and inventory management goals. It also factors in supplier break points (minimum acceptable prices), current progress toward targets over time, and the desired emphasis on different objectives at specific times. Additionally, the system analyzes competitive market pricing for CPC bids to ensure ads are placed effectively relative to competitors. The bidding algorithm dynamically balances these factors to optimize ad placement and performance without manual intervention. This approach improves efficiency by continuously adjusting bids to align with evolving seller priorities and market conditions, ensuring better return on ad spend and inventory turnover.
13. The method of claim 10 wherein each CPC bid is computed in a manner so as to optimize the seller's unique targets, while simultaneously minimizing the CPC expenditure and without manual intervention and associated inherent speculation while computing the CPC bids, thereby eliminating significant inherent margins of error.
This invention relates to automated cost-per-click (CPC) bid optimization in online advertising, addressing the challenge of balancing seller objectives with cost efficiency. The method dynamically computes CPC bids to meet a seller's unique performance targets, such as conversion rates or return on ad spend, while minimizing advertising expenditure. Unlike traditional approaches that rely on manual adjustments or static algorithms, this system eliminates human intervention and reduces speculative errors by continuously analyzing real-time data. The optimization process considers multiple factors, including historical performance, competitor behavior, and market conditions, to generate bids that maximize efficiency. By automating the bid calculation, the method ensures consistent alignment with seller goals while minimizing wasteful spending. The system also adapts to changing market dynamics, ensuring sustained performance without manual oversight. This approach improves accuracy and reduces the inherent margins of error associated with manual bid management, leading to more effective and cost-efficient advertising campaigns.
14. The method of claim 10 wherein the SAEJ enables instantaneous adaptation and responsiveness to evolving competitive market conditions in terms of ad placement location and corresponding CPC pricing for each set of key words, for each product and for each search engine, such that contribution to the seller's unique business targets is optimized while minimizing expenditure, all of it performed without any manual intervention.
This invention relates to automated search advertising optimization in competitive digital marketing environments. The system dynamically adjusts ad placement locations and cost-per-click (CPC) pricing for keyword sets across multiple products and search engines to maximize business objectives while minimizing costs. The solution continuously monitors market conditions and automatically adapts strategies without manual intervention. It evaluates performance metrics to optimize ad positioning and pricing in real-time, ensuring alignment with the seller's unique business goals. The system handles variations in search engine algorithms, competitor activity, and consumer behavior to maintain optimal ad performance. By automating these adjustments, it reduces operational overhead while improving return on ad spend. The technology is particularly useful for e-commerce platforms and digital marketers managing large-scale advertising campaigns across multiple channels. The core innovation lies in its ability to process vast amounts of real-time data to make instantaneous, data-driven decisions that enhance ad effectiveness and efficiency.
15. The method of claim 10 wherein the pricing decisions on sale automatically and instantaneously adapt to the dynamically altering market place as reflected by the variance in the CTR, and to dynamically altering competitive pressures reflected by the variations in the CPC bid prices, and in a manner to optimize the targets.
This invention relates to dynamic pricing optimization for online advertising, specifically addressing the challenge of adapting pricing decisions in real-time to fluctuating market conditions. The system automatically adjusts pricing based on two key variables: click-through rate (CTR) and cost-per-click (CPC) bid prices. By continuously monitoring these metrics, the system detects changes in market demand and competitive bidding behavior. When CTR varies, it indicates shifts in user engagement, while fluctuations in CPC bid prices reflect competitive pressure. The system processes these inputs to optimize pricing decisions instantaneously, ensuring that advertising targets—such as maximizing revenue or achieving specific conversion goals—are met efficiently. This approach eliminates manual adjustments, improving responsiveness to market dynamics and enhancing campaign performance. The method integrates real-time data analysis with automated decision-making to maintain optimal pricing strategies without human intervention.
16. The method of claim 10 wherein automatic evaluating and ranking of the prevailing CPM bids is according to the contribution to the unique business targets and with minimum expenditure, for each desirable web site for display ads, for each set of contextual key words for each product, and for selected geographical regions simultaneously computing the appropriate product price in addition to the CPM bid to optimize the targets, and with the seller's CPM bid decisions completely synergistic with its unique business targets, while minimizing the expenditure, and while staying within its budgetary constraints.
This invention relates to optimizing online advertising campaigns by automatically evaluating and ranking prevailing CPM (cost-per-thousand impressions) bids to achieve specific business targets while minimizing expenditure. The system computes the optimal product price alongside the CPM bid for each desirable website, set of contextual keywords, and selected geographical region. The evaluation considers the contribution of each bid to unique business objectives, ensuring that the seller's CPM bid decisions align synergistically with these targets. The process operates within predefined budgetary constraints, dynamically adjusting bids to maximize efficiency. The method ensures that advertising efforts are cost-effective and strategically aligned with the seller's goals, improving return on investment while maintaining financial discipline. The system automates the complex decision-making process, allowing advertisers to optimize their campaigns across multiple dimensions—websites, keywords, and regions—simultaneously. This approach enhances targeting precision and reduces wasted ad spend, making online advertising more efficient and results-driven.
17. The method of claim 16 wherein there is provided in real-time dynamic arbitraging of the advertising expenditure among both search engine-based advertising channels and display ad channels, and in a manner which optimizes business targets while minimizing the advertising expenditure, and while staying within the budgetary constraints.
This invention relates to real-time dynamic arbitraging of advertising expenditures across multiple digital advertising channels, including search engine-based advertising and display ad channels. The system optimizes advertising performance by automatically allocating budgets to different channels in real-time to achieve business targets, such as maximizing conversions or return on investment, while minimizing overall advertising costs. The method ensures that the total expenditure remains within predefined budgetary constraints. The dynamic arbitraging process continuously adjusts allocations based on real-time performance data, such as click-through rates, conversion rates, and cost-per-acquisition, to ensure optimal use of advertising funds. The system may also incorporate predictive analytics to forecast future performance and preemptively adjust allocations. By integrating both search and display advertising channels, the method provides a unified approach to budget optimization, reducing inefficiencies and improving overall campaign effectiveness. The solution is particularly useful for advertisers managing large-scale campaigns across multiple platforms, where manual budget adjustments are impractical. The invention ensures that advertising spend is dynamically reallocated to the most effective channels at any given time, maximizing business objectives while staying within financial limits.
18. The method of claim 16 wherein the advertiser has the ability to make a bid on higher quality of leads using sorting buckets at the search engine, optimizing the percentage of bids picked from each such bucket.
This invention relates to online advertising systems, specifically improving the quality of leads generated for advertisers by allowing them to bid on higher-quality leads. The problem addressed is the variability in lead quality, where advertisers often receive leads that do not meet their criteria, leading to wasted ad spend and inefficiency. The system uses sorting buckets to categorize leads based on quality metrics, such as user engagement, relevance, or conversion likelihood. Advertisers can then place bids on leads from specific buckets, adjusting their bid amounts to prioritize higher-quality leads. The system optimizes the selection process by dynamically adjusting the percentage of bids picked from each bucket, ensuring that advertisers receive leads that align with their quality preferences while maintaining cost efficiency. The method involves analyzing lead data to assign quality scores, grouping leads into predefined buckets based on these scores, and allowing advertisers to specify bid amounts for each bucket. The system then selects leads for display based on the bid amounts and the distribution of leads across buckets, ensuring that higher-quality leads are more likely to be presented to advertisers who value them. This approach improves the efficiency of ad spend by reducing the number of low-quality leads and increasing the likelihood of conversions.
19. The method of claim 7 wherein the advertiser is enabled to make iterative competitive bids in response to a specific user query with its unique characteristics instead of making CPC bids in advance in anticipation of a query.
This invention relates to online advertising systems, specifically improving the efficiency of cost-per-click (CPC) bidding by enabling advertisers to make real-time, competitive bids in response to specific user queries rather than pre-submitting bids in anticipation of queries. The problem addressed is the inefficiency of traditional CPC bidding, where advertisers must predict and pre-bid on potential queries, often leading to wasted ad spend or missed opportunities due to mismatched bids and actual user intent. The system allows advertisers to analyze the unique characteristics of a user's query in real time, such as keywords, context, and user behavior, and then submit competitive bids dynamically. This approach ensures that bids are more aligned with the actual value of the query, improving ad relevance and reducing wasted ad spend. The method involves a bidding interface that presents advertisers with query details and allows them to adjust bids iteratively based on real-time data. The system may also incorporate machine learning to suggest optimal bid amounts based on historical performance and competitive landscape. By enabling real-time bidding, advertisers can respond more effectively to fluctuations in demand and competition, leading to higher ad placement accuracy and better return on investment. The invention improves upon traditional CPC models by shifting from static, pre-submitted bids to dynamic, query-specific bidding, enhancing both advertiser efficiency and user experience.
20. A system for optimizing quantitative business objectives and targets of product or service sellers together with synergistic pricing, promotions and advertisements, including one or more of search engine-based advertising, Internet web-based on-line display advertising, and TV advertising, the system having, in combination: one or more seller/advertiser automated, adaptive, real-time computer engines (SAEJ) capable of determining the optimal price that the market will bear at any point of time, and capable of computing such price in real-time in order to optimize each sellers business targets, each SAEJ is capable of evaluating the sellers advertising needs in the context of current cost-per-click (CPC) or cost per thousand impressions (CPM), of the status of said targets, and the current market conditions, each SAEJ is capable of triggering advertisements in response to said evaluating, as and when appropriate, and means for computing bids in real-time, taking into consideration the expense associated with each bid, the current status of said targets, and the requisite pricing needed to optimize said targets, and each SAEJ is capable of automatically and optimally allocating advertising selections in real-time, thereby to optimize allocation of advertising to achieve said targets while minimizing expenditure.
This system optimizes business objectives and targets for product or service sellers by dynamically adjusting pricing, promotions, and advertisements across multiple channels, including search engine-based advertising, online display advertising, and TV advertising. The system employs one or more automated, adaptive, real-time computer engines (SAEJ) that determine the optimal market price at any given time to maximize business targets. These engines evaluate advertising needs based on current cost-per-click (CPC) or cost-per-thousand-impressions (CPM) rates, the status of business targets, and market conditions. They trigger advertisements as needed and compute real-time bids, considering bid expenses, target status, and required pricing to optimize outcomes. The system also automatically allocates advertising selections in real-time to achieve targets while minimizing costs. By integrating pricing and advertising strategies, the system ensures synergistic optimization of business goals across different marketing channels.
21. The system of claim 20 wherein each SAEJ is capable of discovering and rank-ordering the optimal CPC/CPM bids according to the contribution made by each towards meeting the seller's unique targets while simultaneously minimizing advertising expenditure in anticipation of receiving corresponding clicks or leads resulting in consequent business based on an expected conversion rate.
This invention relates to an advertising optimization system designed to improve digital advertising efficiency by dynamically selecting and ranking optimal cost-per-click (CPC) or cost-per-mille (CPM) bids. The system addresses the challenge of balancing advertising expenditure with performance targets, ensuring that bids align with a seller's specific business objectives while minimizing costs. It leverages expected conversion rates to predict the business impact of each bid, allowing for data-driven decision-making. The system evaluates bids based on their contribution to meeting predefined targets, such as revenue, lead generation, or other key performance indicators, while optimizing for cost efficiency. By continuously analyzing bid performance and adjusting selections, the system maximizes return on ad spend (ROAS) and ensures that advertising budgets are allocated to the most effective campaigns. The invention is particularly useful in digital marketing environments where advertisers must navigate complex bidding strategies to achieve measurable business outcomes. The system's ability to rank bids according to their expected value helps sellers optimize their advertising investments while maintaining alignment with broader business goals.
22. The system of claim 21 wherein synergistic computation is affected by the SAEJ of the optimum product or service price for such advertising to further optimize said targets.
The system improves advertising by using a special calculation (SAEJ) to find the best price for the ad, which helps the system target the right people more effectively.
23. The system of claim 22 wherein the SAEJ adjusts such product or service price automatically and in real-time.
A system for dynamic pricing of products or services adjusts prices automatically and in real-time based on supply, demand, or other market conditions. The system includes a pricing engine that processes real-time data inputs, such as inventory levels, competitor pricing, customer behavior, or external factors like weather or economic trends. The engine applies predefined rules or machine learning models to determine optimal price adjustments. These adjustments are then implemented across sales channels, such as online platforms or physical stores, without manual intervention. The system may also incorporate feedback loops to refine pricing strategies over time. This approach ensures competitive pricing, maximizes revenue, and adapts to market fluctuations efficiently. The system may further integrate with inventory management or customer analytics tools to enhance decision-making. By automating price adjustments, businesses can respond swiftly to changing conditions, improving profitability and customer satisfaction. The system is particularly useful in industries with high price volatility, such as retail, hospitality, or digital services.
24. The system of claim 23 wherein the SAEJ automatically and appropriately adjusts ad placement, corresponding CPC bids, number of display ads with corresponding CPM, and simultaneous product or service price adjustment, all within unique seller-provided constraints.
The invention relates to an automated advertising and pricing system designed for online marketplaces. The system addresses the challenge of dynamically optimizing ad placements, pricing strategies, and bid adjustments to maximize revenue while adhering to seller-defined constraints. The system automatically adjusts ad placement, cost-per-click (CPC) bids, the number of display ads with corresponding cost-per-thousand-impressions (CPM), and product or service pricing in real time. These adjustments are made within predefined limits set by sellers, ensuring that the system operates within acceptable boundaries for each seller's business model. The system integrates these adjustments to balance visibility, profitability, and user engagement, improving overall marketplace efficiency. By automating these processes, the system reduces manual intervention, enhances ad performance, and optimizes pricing strategies to adapt to market conditions and user behavior. The solution is particularly useful for e-commerce platforms, digital marketplaces, and advertising networks where dynamic pricing and ad optimization are critical for competitive advantage.
25. The system of claim 24 wherein, following a short term ad promotion, each SAEJ is capable of reverting back to normal mode of operation for both CPC/CPM bids and also that of product or service pricing.
A system for managing short-term advertising promotions in digital advertising platforms addresses the challenge of dynamically adjusting ad pricing and bidding strategies during limited-time campaigns. The system includes a mechanism to temporarily modify the behavior of Standard Ad Exchange Jobs (SAEJs) to support promotional pricing and bidding adjustments, such as cost-per-click (CPC) or cost-per-mille (CPM) bids, during a short-term ad promotion. After the promotion ends, the system automatically reverts each SAEJ back to its normal operating mode, restoring standard pricing and bidding strategies for the advertised products or services. This ensures that promotional adjustments do not persist beyond the intended duration, maintaining consistency in ad performance and financial forecasting. The system may also include features to track and analyze the impact of the promotion, allowing advertisers to optimize future campaigns. The solution is particularly useful for digital advertisers and ad platforms that need to run time-sensitive promotions without disrupting long-term ad strategies.
26. The system of claim 23 wherein the SAEJ optimizes the sellers targets by computing optimal CPC/CPM advertising channel selection, placement and pricing as well as the optimal product or service pricing.
The system automatically figures out the best places to advertise, how much to pay for those ads, and the right price to charge for the product or service being sold, all to help sellers reach their goals.
27. The system of claim 26 wherein said optimizing as effected according to the formula of equations (1) through (26) herein.
This invention relates to an optimization system for improving the performance of a technical process or system. The system addresses the challenge of efficiently optimizing complex processes by using a set of mathematical equations to determine optimal operating parameters. The equations (1) through (26) define the relationships between input variables, constraints, and output performance metrics, allowing the system to calculate the best configuration for maximizing efficiency, minimizing costs, or achieving other desired outcomes. The system may be applied to various domains, such as manufacturing, energy management, or industrial automation, where precise control of variables is critical. By solving these equations, the system dynamically adjusts parameters in real-time or near-real-time to adapt to changing conditions, ensuring optimal performance under varying operational constraints. The equations account for nonlinearities, interdependencies, and external factors, providing a robust framework for decision-making. The system may include sensors, actuators, and computational modules to collect data, apply the optimization equations, and implement adjustments automatically. This approach reduces manual intervention, improves accuracy, and enhances overall system reliability. The invention is particularly useful in environments where traditional optimization methods are computationally intensive or impractical.
28. The system of claim 26 wherein, beyond automatic price discovery, promotion and optimizing across said targets, the SAEJ is operated automatically to computes CPC bid values per product, per set of keywords, per ad placement, per search engine in real-time, all as a function of and synergistically with each of the CPC bid history, prevailing competitive CPC pricing, the sellers time-sensitive objectives and targets, and the prevailing market conditions.
This invention relates to an automated system for optimizing online advertising campaigns, specifically in the domain of cost-per-click (CPC) bidding. The system addresses the challenge of dynamically adjusting CPC bids to maximize advertising efficiency while aligning with a seller's time-sensitive objectives and market conditions. The system computes CPC bid values in real-time for individual products, keyword sets, ad placements, and search engines. These computations are based on multiple factors, including historical CPC bid data, current competitive pricing, the seller's specific goals, and prevailing market conditions. The system operates autonomously to discover optimal pricing, promote effective ad placements, and optimize performance across all targets. By integrating these variables synergistically, the system ensures that bids are not only competitive but also strategically aligned with the seller's objectives, whether short-term or long-term. This real-time adjustment capability enhances the efficiency of advertising spend, improving return on investment (ROI) while reducing manual intervention. The system's ability to adapt to market fluctuations and competitive dynamics ensures sustained performance in dynamic online advertising environments.
29. The system of claim 26 wherein each SAEJ is capable of automatically computing of the optimum CPC bids for each search engine, for each set of key words, for each ad position for each product, and for selected geographical regions.
The system automatically figures out the best prices to bid on ads for each product on different search engines, considering keywords, ad placement, and location.
30. The system of claim 26 wherein each SAEJ is capable of automatically evaluating and ranking of the order the prevailing CPC bids according to the contribution to the unique business targets, with minimum expenditure, and for each search engine, for each set of key words, for each ad position, for each product, and for selected geographical regions.
This invention relates to a system for optimizing online advertising campaigns, specifically focusing on managing cost-per-click (CPC) bids across multiple search engines to achieve business targets with minimal expenditure. The system evaluates and ranks the prevailing CPC bids for each search engine, keyword set, ad position, product, and selected geographical region. It automatically determines the optimal bid order to maximize contributions to unique business objectives, such as revenue, conversions, or brand visibility, while minimizing costs. The system dynamically adjusts bids based on real-time performance data, ensuring that advertising spend is allocated efficiently across different search engines and regions. This approach allows advertisers to optimize their campaigns without manual intervention, improving return on investment (ROI) by aligning bids with specific business goals. The system also supports granular control, enabling customization for individual products, ad positions, and geographical areas to further refine targeting and performance. By automating bid evaluation and ranking, the system reduces the complexity of managing large-scale advertising campaigns while enhancing overall efficiency and effectiveness.
31. The system of claim 29 wherein the CPC bids are automatically computed in real-time as a function of the seller's targets, including revenue, profit, product inventory, supplier's break, current target status as a function of time, desired relative degree of emphasis at that time, and the competitive market pricing for CPC for the desired ad placement.
This invention relates to an automated system for dynamically computing cost-per-click (CPC) bids in online advertising. The system addresses the challenge of optimizing ad placement bids to maximize seller objectives while adapting to real-time market conditions and inventory constraints. The system calculates CPC bids in real-time based on multiple factors, including the seller's revenue and profit targets, product inventory levels, supplier breakpoints (minimum acceptable prices), current progress toward targets over time, the desired emphasis on specific objectives at any given time, and competitive market pricing for the desired ad placement. By integrating these variables, the system ensures bids are both strategically aligned with seller goals and responsive to market dynamics, improving ad placement efficiency and return on investment. The system may also incorporate additional constraints or priorities, such as inventory turnover rates or supplier agreements, to further refine bid calculations. This approach automates the bid optimization process, reducing manual intervention and enhancing the precision of ad campaign performance.
32. The system of claim 29 wherein each CPC bid is computed in a manner so as to optimize the seller's unique targets, while simultaneously minimizing the CPC expenditure and without manual intervention and associated inherent speculation while computing the CPC bids, thereby eliminating the significant inherent margins of error.
This invention relates to automated cost-per-click (CPC) bid optimization in online advertising systems. The problem addressed is the inefficiency and inaccuracy of manual CPC bid management, which often leads to suboptimal ad performance, wasted ad spend, and significant margins of error due to human speculation. The system automatically computes CPC bids to optimize a seller's unique performance targets, such as conversion rates or return on ad spend, while minimizing the overall CPC expenditure. The optimization process operates without manual intervention, eliminating the need for human judgment and reducing errors associated with manual bid adjustments. The system dynamically adjusts bids based on real-time data and performance metrics, ensuring that ad campaigns align with the seller's objectives while controlling costs. This approach improves ad efficiency, reduces wasteful spending, and enhances overall campaign performance by leveraging automated, data-driven bid optimization. The system is particularly useful in digital advertising platforms where precise bid management is critical for maximizing return on investment.
33. The system of claim 29 wherein the SAEJ enables instantaneous adaptation and responsiveness to evolving competitive market conditions in terms of ad placement location and corresponding CPC pricing for each set of key words, for each product and for each search engine, such that contribution to the seller's unique business targets is optimized while minimizing expenditure, all performed without any manual intervention.
This invention relates to an automated system for optimizing ad placement and pricing in digital advertising. The system addresses the challenge of dynamically adjusting ad campaigns to respond to competitive market conditions, ensuring optimal performance while minimizing costs. The system uses a self-adjusting engine (SAEJ) that automatically adapts ad placement locations and cost-per-click (CPC) pricing for specific keywords, products, and search engines. This adaptation occurs in real-time, allowing the system to maximize the seller's business objectives, such as revenue or conversion rates, while minimizing advertising expenditure. The SAEJ operates without manual intervention, continuously analyzing market conditions and adjusting parameters to maintain optimal performance. The system also includes a data collection module that gathers performance metrics and competitor data, which the SAEJ uses to refine its decisions. Additionally, the system may incorporate a predictive model to forecast future market trends, further enhancing its ability to preemptively adjust strategies. The overall goal is to achieve the highest possible return on investment (ROI) for digital advertising campaigns by leveraging automated, data-driven optimizations.
34. The system of claim 29 wherein each SAEJ is capable of enabling the pricing decisions to be made automatically and instantaneously to adapt to the dynamically altering market place as reflected by the variance in the CTR, and to dynamically altering competitive pressures reflected by the variations in the CPC bid prices, and in a manner to optimize the targets.
This invention relates to an automated pricing system for digital advertising, specifically addressing the challenge of dynamically adjusting pricing decisions in response to real-time market conditions. The system leverages a self-adjusting engine (SAEJ) to enable instantaneous pricing adjustments based on changes in click-through rates (CTR) and cost-per-click (CPC) bid prices. The SAEJ continuously monitors these metrics to adapt pricing strategies automatically, ensuring optimal performance targets are met despite fluctuating market conditions and competitive pressures. The system integrates with a broader framework that includes a data collection module for gathering performance metrics, a processing module for analyzing these metrics, and an optimization module for adjusting pricing parameters. The SAEJ operates within this framework to dynamically recalibrate pricing decisions, ensuring alignment with real-time market dynamics and competitive bidding environments. This approach enhances efficiency by eliminating manual intervention, allowing advertisers to maintain competitive pricing while maximizing return on investment. The system is particularly suited for digital advertising platforms where rapid response to market changes is critical for success.
35. The system of claim 29 wherein automatic evaluating and ranking of the prevailing CPM bids is according to the contribution to the unique business targets and with minimum expenditure, for each desirable web site for display ads, for each set of contextual key words for each product, and for selected geographical regions simultaneously computing the appropriate product price in addition to the CPM bid to optimize the targets, and with the seller's CPM bid decisions completely synergistic with its unique business targets, while minimizing expenditure, and staying within its budgetary constraints.
This invention relates to an automated system for optimizing online advertising campaigns by evaluating and ranking CPM (cost-per-thousand impressions) bids based on unique business targets while minimizing expenditure. The system simultaneously computes the optimal product price alongside the CPM bid to maximize the effectiveness of ad placements. It considers multiple variables, including desirable websites for display ads, contextual keywords for each product, and selected geographical regions, to ensure alignment with the seller's business objectives. The system ensures that the seller's CPM bid decisions are fully synergistic with their unique goals, such as maximizing conversions, brand awareness, or revenue, while adhering to budgetary constraints. By dynamically adjusting bids and pricing, the system optimizes ad performance across different contexts and regions, ensuring cost-efficient targeting. The approach integrates real-time data analysis to refine bid strategies, enhancing the overall return on advertising investment. This solution addresses the challenge of balancing performance optimization with budget limitations in digital advertising campaigns.
36. The system of claim 35 wherein there is provided in real-time dynamic arbitraging of the advertising expenditure among both, search engine-based advertising channels and display ad channels, and in a manner which optimizes business targets while minimizing the advertising expenditure, and while staying within the budgetary constraints.
The system dynamically allocates advertising expenditures in real-time across both search engine-based advertising channels and display ad channels. The system optimizes business targets, such as maximizing return on investment or click-through rates, while minimizing overall advertising costs. It ensures that the allocation remains within predefined budgetary constraints. The system continuously monitors performance metrics from both advertising channels and adjusts the budget distribution to capitalize on the most cost-effective opportunities. This real-time arbitrage ensures that advertising spend is optimized for efficiency and effectiveness, balancing performance across different ad formats while adhering to financial limits. The system may also incorporate predictive analytics to forecast future performance trends and preemptively adjust allocations to maintain optimal results. By dynamically reallocating funds between search and display ads, the system maximizes the impact of each advertising dollar while ensuring budget compliance. This approach enhances campaign performance by leveraging real-time data to make informed, automated decisions.
37. The system of claim 35 wherein each SAEJ is capable to enable the advertiser to make a bid on higher quality of leads using sorting buckets at the search engine, optimizing the percentage of bids picked from each such bucket.
This invention relates to a system for optimizing lead quality in online advertising, particularly for search engine advertising. The problem addressed is the inefficiency in bid allocation for high-quality leads, where advertisers often struggle to effectively target and secure the most valuable user interactions. The system enhances a search engine advertising platform by introducing sorting buckets that categorize leads based on quality metrics. Each Sorting Advertising Engine (SAEJ) allows advertisers to bid on leads from these buckets, optimizing the distribution of bids across different quality tiers. The system dynamically adjusts bid selection percentages from each bucket to maximize the advertiser's return on investment by prioritizing higher-quality leads. The SAEJ operates within the search engine's infrastructure, ensuring seamless integration with existing advertising workflows. The invention improves lead targeting precision and reduces wasted ad spend by focusing bids on the most valuable user segments. This approach benefits both advertisers, who achieve better campaign performance, and the search engine, which can offer more efficient and profitable advertising services. The system is designed to be scalable and adaptable to various advertising models, ensuring broad applicability across different industries and use cases.
38. The system of claim 26 wherein each SAEJ is capable to enable the advertiser to make iterative competitive bids in response to a specific user query with its unique characteristics instead of making CPC bids in advance in anticipation of a query.
39. A method of optimizing quantitative business objectives and targets of product or service sellers together with synergistic pricing, promotions and advertisements, including one or more of search engine-based advertising, Internet web-based on-line display advertising, and TV advertising, the method comprising: providing the seller/advertiser with an automated, adaptive, real-time engine (SAEJ) capable of determining the optimal price that the market will bear at any point of time, and capable of computing such price in real-time in order to optimize the sellers business targets; evaluating the sellers advertising needs in the context of current cost-per-click (CPC) or cost per thousand impressions (CPM) prices, of the status of said targets, and the current market conditions; triggering advertisements in response to said evaluating, as and when appropriate, and computing bids in real-time, taking into consideration the expense associated with each bid, the current status of said targets, and the requisite pricing needed to optimize said targets; automatically and optimally allocate advertising selections in real-time, thereby to optimize allocation of advertising to achieve said targets while minimizing expenditure; wherein the optimal CPC/CPM bids are discovered and rank-ordered according to the contribution made by each towards meeting the seller's unique targets while simultaneously minimizing advertising expenditure in anticipation of receiving corresponding clicks or leads resulting in consequent business based on an expected conversion rate; wherein synergistic computation is affected by the SAEJ of the optimum product or service price for such advertising to further optimize said targets; wherein the SAEJ is caused to adjust such product or service price automatically and in real-time; wherein the SAEJ is caused to optimize the sellers targets by computing optimal CPC/CPM advertising channel selection, placement and pricing as well as the optimal product or service pricing; and wherein said optimizing as effected according to the formula of equations (1) through (26) herein.
This invention relates to a system for optimizing business objectives and targets for product or service sellers by dynamically adjusting pricing, promotions, and advertising strategies across multiple channels, including search engine advertising, online display advertising, and TV advertising. The system addresses the challenge of maximizing revenue and minimizing costs by integrating real-time market analysis with automated decision-making. The core of the invention is an automated, adaptive, real-time engine (SAEJ) that determines the optimal market price for a product or service at any given time. The engine evaluates advertising needs based on current cost-per-click (CPC) or cost-per-thousand-impressions (CPM) rates, market conditions, and the seller's business targets. It triggers advertisements and computes bids in real-time, considering advertising costs, target status, and pricing adjustments to optimize business outcomes. The system optimally allocates advertising selections across channels, prioritizing those that contribute most to meeting the seller's targets while minimizing expenditure. It ranks bids based on their expected conversion rates and business impact, ensuring cost-effective advertising. Additionally, the engine adjusts product or service pricing in real-time to further enhance target optimization. The entire process is governed by a set of mathematical equations (1 through 26) that define the optimization logic. This approach ensures that pricing, promotions, and advertising work synergistically to maximize profitability and efficiency.
40. A system for optimizing quantitative business objectives and targets of product or service sellers together with synergistic pricing, promotions and advertisements, including one or more of search engine-based advertising, Internet web-based on-line display advertising, and TV advertising, the system having, in combination: a plurality of seller/advertiser automated, adaptive, real-time engines (SAEJ) capable of determining the optimal price that the market will bear at any point of time, and capable of computing such price in real-time in order to optimize each sellers business targets; means for evaluating the sellers advertising needs in the context of current cost-per-click (CPC) or cost per thousand impressions (CPM), of the status of said targets, and the current market conditions; means for triggering advertisements in response to said evaluating, as and when appropriate, and means for computing bids in real-time, taking into consideration the expense associated with each bid, the current status of said targets, and the requisite pricing needed to optimize said targets; means for causing the SAEJ thereupon automatically and optimally to allocate advertising selections in real-time, thereby to optimize allocation of advertising to achieve said targets while minimizing expenditure; wherein means is provided whereby the optimal CPC/CPM bids are discovered and rank-ordered according to the contribution made by each towards meeting the seller's unique targets while simultaneously minimizing advertising expenditure in anticipation of receiving corresponding clicks or leads resulting in consequent business based on an expected conversion rate; wherein synergistic computation is affected by the SAEJ of the optimum product or service price for such advertising to further optimize said targets; wherein the SAEJ is caused to adjust such product or service price automatically and in real-time; wherein the SAEJ is caused to optimize the sellers targets by computing optimal CPC/CPM advertising channel selection, placement and pricing as well as the optimal product or service pricing; and wherein said optimizing as effected according to the formula of equations (1) through (26) herein.
The system optimizes business objectives and targets for product or service sellers by dynamically adjusting pricing, promotions, and advertisements across multiple channels, including search engine advertising, online display ads, and TV advertising. The system employs automated, adaptive, real-time engines (SAEJ) that determine the optimal market price for products or services at any given time, computing these prices in real-time to align with sellers' business goals. It evaluates advertising needs based on current cost-per-click (CPC) or cost-per-thousand-impressions (CPM) rates, market conditions, and the status of the seller's targets. The system triggers advertisements when appropriate and computes bids in real-time, considering bid expenses, target status, and pricing requirements to optimize outcomes. Advertising selections are automatically allocated in real-time to maximize target achievement while minimizing costs. The system discovers and rank-orders optimal CPC/CPM bids based on their contribution to meeting the seller's unique targets while minimizing advertising expenditure, anticipating clicks or leads and their expected conversion rates. Synergistic computation adjusts product or service prices in real-time to further optimize targets. The SAEJ optimizes advertising channel selection, placement, pricing, and product/service pricing using a defined set of equations to ensure alignment with business objectives.
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October 16, 2007
August 27, 2013
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